Construction Of Charging Stations Research Articles

Suitable law-based location selection of high-power electric vehicles charging stations on the TEN-T core network for sustainability: a case of Poland

With the upcoming implementation of the amendment to Regulation (EU) 2019/631 of the European Parliament and of the Council, from 2035 there will be a ban on the registration of new vehicles with internal combustion engines (ICE) in the Member States of the European Union (EU). Consequently, changes in the transportation sector, resulting from the increasing use of electric vehicles, appear to be inevitable. According to the adopted legal acts, the European Union Member States will be obliged to develop, among others, a charging infrastructure and access to public charging stations for electric vehicles. As a result, there will be a need to ensure a significant increase in the power and the number of charging stations and to determine their appropriate location. The article presents the challenges faced by charging station operators and difficulties related to the further development of electric vehicle charging infrastructure in Poland. The still poorly developed public charging infrastructure for electric vehicles, especially in service areas located along the main communication routes, remains the main obstacle to the development of electromobility. In the context of legal, financial, technological, and organizational challenges, the problem of the proper distribution of electric vehicle charging stations along the main communication routes is therefore of particular importance. The aim of the article is to present a new, proprietary method for determining the location of electric vehicle charging stations in Poland within the Trans-European Transport Network (TEN-T), which considers objective location factors: adherence to AFIR requirements, the specificity of the Polish power system and existing parking infrastructure. As a result of using the developed method, a list of 188 recommended locations for the construction of electric vehicle charging stations in Poland along the Trans-European Transport Network (TEN-T) was created. It has been shown in this way that the use of the presented method enables the suitable determination of the location of electric vehicle charging stations along transport routes, considering legal, financial, and technological requirements, which will significantly facilitate the operation of zero-emission transport.

Electric vehicle battery-charging service and operations managing under different charging station construction modes

Using electric vehicles (EVs) is considered as an effective way to reduce carbon emissions. In practice, (self) charging-mode EVs (CEVs) require a long charging time, which has led to the emergence of (battery) swapping-mode EVs (SEVs). This study first discusses whether the manufacturer should introduce SEVs and identifies the introduction conditions. Further, it investigates the impact of two construction modes (manufacturer-construction mode and commission-construction mode) of energy replenishment stations on pricing decisions, EVs demand, and profits. Finally, we optimize the government subsidy level to minimize the total capital expenditure for a specific EVs adoption target. The results reveal that introducing SEVs can bring more stations, higher retail price and charging service fee for CEVs, as well as greater demand for EVs when the unit production cost of CEVs is high. If the consumers’ preference for SEVs is low, introducing SEVs can increase profits in most cases; if the consumers’ preference for SEVs is high, introducing SEVs is detrimental to the EVs manufacturer only when the government subsidy is not too high. Comparing to the commission-construction mode, the manufacturer-construction mode can bring more stations, higher total demand for EVs, and higher total profits; meanwhile, it can lower the optimal subsidy level of the government.

Design of Charging Station Information Monitoring System based on CAT.1

Intelligent charging station information monitoring system is significant to the construction of intelligent charging stations. A charging station information monitoring system is designed based on 4G CAT.1. Sensors are used to detect different information like electricity usage and positioning. A rely is also used to control the charging station by receiving remote control signal from cloud platform. After debugging, the system can realize the remote information monitoring.

The impact of green consumers on electric vehicle charging station diffusion based on complex network evolutionary game

The disparity between the supply and demand for public charging stations impedes road vehicle electrification. The public charging station, a socially produced artefact, is subject to customer preferences and government regulatory limits. However, traditional knowledge does not completely capture the complex dynamics behind the public charging station investment, and a combined interactive decision review is inadequate. To examine enhanced dynamic interactions, this paper provides a complex network evolutionary game model. According to the findings, subsidies for charging infrastructure construction are more vital than electric vehicle subsidies. Under present market conditions, removing the electric vehicle subsidy reduces the market percentage of charging stations by 6%, whereas removing the charging station construction incentive results in a 35% decline. Second, charging price and charging station diffusion has an inverted U-shaped relationship, and increasing the oil price slows charging station dispersion. Third, the construction cost has less of an influence on charging station diffusion. Finally, green consumer preferences are the key driver of public charging station investment. An increase in consumer preference from 0.17 to 0.38 would lead to a 30% increase in the market share of the charging station industry from 53% to 83%. Based on these results, policy implications for the investment in public charging stations are discussed.

Including research on optimization planning of multi-energy complementary electric vehicle charging station

With the enhancement of environmental protection and the incentive policies issued by governments, the choice of electric vehicles as a means of transportation has gradually become a new mode, so the establishment of a perfect charging station service network is a key link and an critical guarantee for accelerating the adoption of electric vehicles (EVs). In the early stage of EV charging station construction, reasonable and scientific planning is not only related to the convenient travel of users, but also related to the effective utilization of resources. To promote the development of low-carbon economy, this paper first propose a Voronoi diagram based charging station service division approach, followed by a M/G/K queuing model based approach for evaluating the charging capacity of the EV charging station. Finally, a location and volume model is constructed and solved to determine the optimal construction plan of the EV charging station with minimum total cost for the whole society. The experimental results show that the charging station planning method proposed in this paper is economical and effectively improves the charging convenience of electric vehicle users. The reasonable location setting and capacity configuration of charging stations promote the sustainable development of the power grid in the planning area, which has certain practical significance.

Probabilistic double hierarchy linguistic MADM for location selection of new energy electric vehicle charging stations based on the MSM operators

The emergence of new energy electric vehicles (NEEV) can effectively reduce vehicle fuel consumption and alleviate the contradiction between fuel supply and demand. It has made great contributions to improving the atmospheric environment and promoting the development of environmental protection. However, the insufficient number of new energy electric vehicle charging stations (NEEVCSs) and unreasonable coverage areas have become obstacles to the large-scale promotion of new energy electric vehicles. Therefore, we build a multi-attribute decision making (MADM) model based on probabilistic double hierarchy linguistic weight Maclaurin symmetric mean (PDHLWMSM) operator and a MADM model based on probabilistic double hierarchy linguistic weight power Maclaurin symmetric mean (PDHLWPMSM) operator to select the best charging station construction point from multiple alternative sites. In addition, the model constructed in this paper is compared with the existing MADM models to verify the scientificity of the model proposed in this paper.

Sustainable construction project of electric vehicle charging stations: A risk-based hybrid decision-making approach

Nowadays, a serious environmental challenge is the pollution emitted by combustion engine vehicles. Governments have found that replacing these with electric vehicles (EVs) is a viable solution for sustainable transportation. The sustainable operation of fast charging stations for EVs is a critical parameter in these vehicles' popularity. Herein, a propose a model for the sustainable evaluation of energy sources of charging stations based on the R-numbers and combined compromise solution method (R–COCOSO). The construction of EV charging stations is done based on new and developing technologies, and they are often expensive, complex, and high-risk. Thus, we developed the combinative distance-based assessment (CODAS) method based on R-numbers to assess the project risk. Moreover, a linear programming model was developed to assess the contractors’ risk response and the optimal allocation of their workload based on R-numbers and the ε− constraint approach. A real case of building charging stations in Tehran, Iran, was presented to test the accuracy of the model.

Bi-level programming model approach for electric vehicle charging stations considering user charging costs

• A new bi-level planning model is proposed that integrates the interests of both charging station investors and EV users, where the upper model has the global economic return as the optimization objective, and the lower model has the EV user's satisfaction with the charging service (charging cost) as the optimization objective. The global economic cost is optimized while the service satisfaction of the user is improved. • The time cost, economic cost, and mileage anxiety are considered together to characterize the service satisfaction of EV users. Specifically, the charging queuing time, driving distance, desired charging volume, and actual charging volume are used to reflect the charging cost of EV users and to reflect the autonomy of EV users more accurately, and a combination of fast and slow charging posts are used for planning to meet the needs of different users and grid constraints, to improve the operational efficiency of charging stations and reduce the charging queuing time of EV users. • The conventional method and the bi-level planning method are solved separately for a region of Beijing, and the effectiveness of the proposed method is verified by comparing factors such as investors' returns, users' charging costs, and queuing times. The rapid development of electric vehicles (EV) has placed greater demands on the planning and construction of public electric vehicle charging stations (EVCS). As EV users are highly autonomous in their charging behavior, the interests of investors and EV users are mutually affected and challenging to balance. Therefore, this paper proposes a bi-level planning model to balance the interests of investors and EV users and optimize global economic costs while improving the service satisfaction of users. The upper-level model aims to optimize the economic cost. In contrast, the lower-level model aims to optimize the service satisfaction of EV users and characterizes the charging satisfaction of EV users through the costs of charging queuing time, distance traveled, desired to charge volume, and actual charging volume, to more accurately reflect the autonomy of EV users. A combination of fast and slow charging piles is also used for planning to meet the needs of different users and improve charging stations' operational efficiency. Finally, a case study is conducted in an area of Beijing to verify that the optimization model has the advantages of low global economic cost, short charging queuing time for users, and high service satisfaction.

Promoting electric vehicles: Reducing charging inconvenience and price via station and consumer subsidies

Environmental and energy independence concerns lead to government subsidies for electric vehicles (EVs). Operational decisions for a government are (i) to incentivize EV ownership by a direct consumer subsidy, a station subsidy that reduces charging inconvenience, or by both subsidies; and (ii) to minimize subsidy expenditure or to maximize EV adoption level. We model the interactions between the government and the charging supplier as a Stackelberg game and study the optimal structure of subsidies by incorporating charging inconvenience. We prove that this inconvenience is decreasing convex in the number of stations. In the expenditure minimization case, the optimal policy depends on the government adoption target and the charging station construction cost. If the adoption target is below a threshold that depends on the construction cost, the government provides pure consumer subsidy or no subsidy; otherwise, a combination of consumer and station subsidies is optimal. As the construction cost increases, the charger builds fewer stations, regardless of the subsidy type. We establish that expenditure minimization and adoption maximization yield the same subsidy policy if the charging inconvenience is linear. In a real‐life case, we find numerically that a station subsidy alone is optimal if the construction cost is not low but the adoption target is low. Besides, a long driving range reduces the need for subsidies significantly if the construction cost is high, whereas a long charging time necessitates high expenditure allocated mostly to a station subsidy.

Site selection for shared charging and swapping stations using the SECA and TRUST methods

With the increase in electric vehicle sales, the construction of charging and switching stations has caused unnecessary waste of land resources and load on the power grid, so it is necessary to consider the “centralized charging and unified distribution” model. Based on this, this paper proposes a shared charging and switching station model under the “centralized charging and unified distribution” model, in which centralized charging stations are built in suburban areas, and switching stations are built in urban areas. This model allows horizontal transfer between switching stations and establishes corresponding site selection decision guidelines. Considering that the existing charging and switching infrastructure can be converted into shared charging and switching station facilities, the MCDM (Multi-Criteria Decision Making) method is used to select sites for shared charging and switching stations. The SECA method is used to determine the weight of each secondary criterion, and the TRUST method is used to rank the alternatives. The results show that the traffic flow and the impact on the residents’ lives are important influencing factors for the location of the shared charging station, and the results show that the optimal solution is A4. Sensitivity analysis is performed by calculating the weight of each criterion or subjective assignment by different MCDM methods. The results prove that the improved method can obtain more objective optimal solutions and analyze when The results prove that the improved method can obtain more objective optimal solutions and analyze the change in solution ranking when decision-makers value different indicators.

Short-term Forecast of EV Ownership in Shanghai Based on Metabolic GM(1,1)-Markov Model

The reasonable forecast of Electric Vehicle (EV) ownership is conducive to grasping the market development and determining the development goals of EVs. In addition, predicting the scale of EVs is conducive to analyzing the impact of EV charging on power grid load and guiding the construction of EV charging stations and other infrastructure. In view of the low amount of EV ownership data over the years in Shanghai, an improved grey model(GM)-Markov prediction method is proposed to predict the ownership of EVs. Firstly, several sets of data at recent time points are selected and the metabolic GM(1,1) replaces the original GM model for data fitting. After obtaining the fitting results, a group of data with the highest fitting accuracy was selected to establish the Markov correction model. Secondly, the Markov correction model is established for the highest fitting accuracy data. The sample mean-standard deviation method is used to divide the state matrix, and the interval partition criterion is dynamically adjusted to fit the relative error distribution probability, which avoids certain subjectivity. Compared with the original model, the relative error of fitting results decreases from 4.780% to 0.764%, and the prediction accuracy of the modified model is further improved. Finally, the ownership of EVs in Shanghai by the Metabolic GM(1,1) -Markov model in the next three years is forecasted, and the ownership of EVs in Shanghai is expected to exceed 1 million in 2023.

Research on Restrictive Factors and Planning of Charging Piles for Electric Vehicles in the Park Based on the Interpretative Structural Model

At present, the world is vigorously promoting the innovative development concept of “green development, park first,” prompting the park to vigorously promote the construction of electric vehicle charging stations and charging pile projects. However, the development of the construction is not satisfactory due to a series of restrictive factors. Under this background, this article studies the constraints of EV charging stations in the park and further studies the impact on park planning. First, this article outlines the constraints of charging piles in the park based on the field research. Then, interpretive structural modeling (ISM) is adopted in this article for in-depth analysis of the restrictive factors. Finally, the impact on the industrial park’s planning is analyzed as a case study. The improved countermeasures provide a basis for the scientific planning and design of electric vehicle charging stations in industrial parks.

A framework for the assessment of electric bus charging station construction: A case study for Stockholm's inner city

Electromobility has gained momentum in the last years following the efforts to reduce transportation-related emissions. In this context, efficient charging infrastructure is vital to foster the expansion of electric vehicles. This paper presents a standardized framework for micro-scale analysis of potential charging locations for electric buses aiming at easing the analysis process and promoting the expansion of electric buses. The framework is tailor-made for the Municipality of Stockholm and tested in two city-centre public transport hubs, namely Odenplan and Slussen. However, the framework can be used in other locations by implementing minimum changes. Connecting charging stations to the power grid is identified as the main drawback in city-centre locations due to their high impact on the grid. Lack of available capacity at nearby connection points results in long distance connections, reaching up to 1 km in some cases. Such connections impact the overall cost of electrification directly, as they may account for up to 63% of the total cost. Although other issues regarding space availability and operational efficiency also need to be addressed, such as the lack of enough dwell time to charge the batteries, the framework proves the suitability of these inner-city locations as charging points.

Coordinating Installation of Electric Vehicle Charging Stations between Governments and Automakers

Accessibility of electric vehicle (EV) charging stations is an important factor for adoption of EV, which is an effective green technology for reducing carbon emissions. Recognizing this, many governments are contemplating ideas for achieving EV adoption targets, such as constructing extra EV charging stations directly or offering subsidies to entice automakers to construct more EV charging stations. To achieve these targets, governments need to coordinate with automakers to ensure that the total number of charging stations is planned optimally. We study this coordination problem by considering the interactions among the government, automakers, and consumers, our equilibrium analysis yields three major results. First, both the government and the automaker should build extra EV charging stations when their construction costs are independent. Simultaneously, the government should offer a per‐station subsidy to the automaker only when the adoption target and the construction cost are both high. However, when the construction costs are dependent, the government should delegate the construction to the automaker by offering a per‐station subsidy. Second, when the government considers consumer purchase subsidy as an extra lever, we find that the purchase subsidy for consumers is more cost‐effective than offering a per‐station subsidy to the automaker. Third, the structure of the optimal government policy remains the same regardless of whether the government's goal is to improve EV adoption or consumer welfare. Our results can serve as guidelines for governments when contemplating coordination with automakers for the construction of EV charging stations to improve EV adoption as well as consumer welfare further.

Research on Ratio of New Energy Vehicles to Charging Piles in China

With the widespread of new energy vehicles, charging piles have also been continuously installed and constructed. In order to make the number of piles meet the needs of the development of new energy vehicles, this study aims to apply the method of system dynamics and combined with the grey prediction theory to determine the parameters as well as to simulate and analyze the ratio of vehicles to chargers. Through scenario analysis, it is predicted that by 2030, this ratio will gradually decrease from 1.79 to 1. In order to achieve this ratio as 1:1, it is necessary to speed up the construction of public charging station or private charging station. Due to global warming, the attitudes of countries towards fuel vehicles have become increasingly tough. There is huge uncertainty in the growth rate of electric vehicles. Therefore, it is recommended that the construction of charging station be deployed in advance to avoid hindering the development of electric vehicles in the future.

Promoting green transportation under the belt and Road Initiative: Locating charging stations considering electric vehicle users’ travel behavior

Motivated by the worldwide promotion of green transportation, this study aims to determine the optimal location of multi-type electric vehicle (EV) charging stations, e.g., fast and slow charging stations, for maximizing the covered traffic flows under a limited budget while considering EV users' partial charging behavior and elastic demand. A two-phase approach is proposed to efficiently solve this problem. The efficacy of the proposed two-phase approach is demonstrated by numerical experiments on the highway network of Zhejiang Province, China, and policies towards promoting transport electrification are discussed from various aspects. In particular, our policy suggestions are fivefold: (a) how to save investment in station construction by understanding EV users’ tolerance for travel cost deviation; (b) how to determine the budget policy to ensure an efficient utilization of the investment; (c) how to optimally select the location and type of charging stations; (d) how to devise the operation regulations based on the workload of each station; as well as (e) how to plan the station construction in a mid- or long-term implementation. We also discuss some prospective challenges and opportunities regarding charging station construction and operations in the context of continuous innovation in energy and communication technologies such as the Internet of Things (IoT).

Two-stage optimal allocation of charging stations based on spatiotemporal complementarity and demand response: A framework based on MCS and DBPSO

This paper studies a two-stage model for the optimization of charging scheduling and charging station construction planning based on the spatial-temporal complementarity of charging demand, in order to improve the overall satisfaction of the whole society. In the first stage, starting from the probability of trip starting point and other characteristics, the simulation of load demand is realized based on Monte Carlo simulation, and the charging plan regulation method is created combined with the principle of Dijkstra algorithm. In the second stage, a solution path based on discrete binary particle swarm optimization is proposed. The experimental results of 14 scenarios show that no matter disorderly charging or orderly charging, the annual social comprehensive cost of the scenario with five charging stations is the lowest. Compared with disordered charging, the total construction capacity of charging station is reduced by 51.61%, and the annual social comprehensive cost is reduced by 29.35%. Therefore, this study provides a framework for the optimal configuration of charging stations, which is applicable when considering or not considering demand response, and provides a solution for the future green development planning of urban charging infrastructure.

Bi-level planning for distribution network including distributed generations and electric vehicle charging stations to meet the requirements of internet of things construction

With the development of power internet of things technology, the application of internet of vehicles technology in the field of electric vehicles (EVs) is constantly maturing and improving. In line with the concept of building an environment-friendly society, distributed generations (DGs) and EVs are being built and put into use in large numbers. In this context, in order to improve the accuracy of distribution network planning, this paper proposes a distribution network planning method based on big data technology. The upper layer aims to minimize the present value of the comprehensive cost of the distribution network, and the lower layer aims to minimize the construction, operation, and maintenance costs of electric vehicle charging stations (EVCSs) and DGs. Under the constraint of relevant constraints, the optimal grid structure of the distribution network including DGs and EVCSs is obtained. The effectiveness of the proposed method is demonstrated using a 54-bus distribution system.

Do policy incentives drive electric vehicle adoption? Evidence from China

The emerging electric vehicle (EV) industry has received enormous support from global governments for its advantages in energy conservation and carbon emission reduction. This paper focuses on the development of the EV industry in China and empirically examines the impact of the government’s incentives on EV adoption in both the public and private domains using data from 61 cities spanning 2009–2018. EV-supportive policies, including financial incentives and convenience measures, are discussed, and a variable instrumental strategy is applied to solve the endogenous problem of charging facilities. The results reveal that in the public domain, financial subsidies can effectively promote the use of electric buses; however, the adoption of commercial EVs is mainly stimulated by charging facility construction and increasing fuel prices. Meanwhile, in the private domain, convenience measures, such as charging station construction and non-purchase limitations, contribute to increasing the demand for EVs, while the effect of financial incentives is not as significant as we expected.

Research on Electrical Technology Schemes for Construction of Charging and Swapping Stations in Alpine Regions

Influenced by policies, resources and environmental factors, the development of electric vehicles has been in an upsurge in these years. Compared with conventional vehicles, electric buses better meet the needs of environmental protection and contribute more to environmental well-being. The State Grid Liaoning Electric Power Supply Company, to promote the use of electric buses, has built many charging and swapping stations in Dalian, which has significant impact on the application of electric buses. To meet the needs of increasing electric buses, this paper mainly discusses the design schemes of the charging and swapping stations of Youyi Street in Dalian, and finally chooses the scheme of “entering the station for swapping-decentralized charging” through comparison in the design.